Application of neuro-fuzzy systems for the solution of radiative transfer inverse problems / Aplicação de redes neuro-fuzzy para a solução de problemas inversos em transferência radiativa

AUTOR(ES)
DATA DE PUBLICAÇÃO

2010

RESUMO

In this thesis is proposed an implementation for solving the inverse problem with the estimates of radiative properties (the single scattering albedo, the optical thickness of the media and the diffuse reflectivities) by the values of the intensities of radiation that leaves the participant medium using a hybrid approach of neuro-fuzzy systems, which combines the use of fuzzy inference systems with artificial neural networks. The use of this hybrid system try to include the ability of fuzzy systems in the treatment of inaccurate, imprecise, and vague data, and the ability of artificial neural networks to deal with learning from experience and widespread knowledge. Also is proposed a methodology for machines committees in neuro-fuzzy solution of this inverse problem in radiative transfer. It was observed in parallel that the solution of neuro-fuzzy systems and hybrid systems neuro-fuzzy committee machines, have a poor quality results when using the experimental data with the lowest sensitivity coefficients for the parameters that will be estimated. Moreover, when data are used with greater sensitivity, better results are obtained. This approach seeks to avoid the possibility of non-convergence in such methods.

ASSUNTO(S)

radiação - transferência máquinas de comitê committee machines problemas inversos (equações diferenciais) neural networks (computer science) fuzzy logic sensitivity analysis lógica difusa modelos analiticos e de simulacao inverse problems (differential equations) análise de sensibilidade radiative transfer redes neurais (computação)

ACESSO AO ARTIGO

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